Update app.py

app.py

@@ -23,25 +23,24 @@ def flux_krea_generate(
     height: int = 1024
 ) -> Optional[Image.Image]:
     """
-    Generate high-quality images using the FLUX.1-Krea-dev model from Hugging Face.
-    
-    This function creates detailed, ultra-high-quality images based on text prompts using 
-    the advanced FLUX.1-Krea-dev diffusion model. The generated images feature ultra detail,
-    ultra elaboration, and perfect quality.
-    
+    Text-to-image generation with FLUX.1-Krea-dev (no input image required).
+
+    This tool generates a single image from a text prompt using the
+    black-forest-labs/FLUX.1-Krea-dev model on Hugging Face Inference.
+
     Args:
-        prompt: Text description of the image to generate. Be detailed and descriptive for best results.
-        negative_prompt: Text describing what should NOT appear in the image. Helps avoid unwanted elements.
-        steps: Number of denoising steps (1-100). Higher values generally produce better quality but take longer.
-        cfg_scale: Classifier-free guidance scale (1-20). Higher values follow the prompt more closely.
-        sampler: Sampling method to use. Options: "DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM".
-        seed: Random seed for reproducible results. Use -1 for random seed.
-        strength: Strength of the generation process (0-1). Higher values give more creative freedom.
-        width: Width of generated image in pixels (64-1216, must be multiple of 32).
-        height: Height of generated image in pixels (64-1216, must be multiple of 32).
-    
+        prompt: Text description of the image to generate.
+        negative_prompt: What should NOT appear in the image.
+        steps: Number of denoising steps (1-100). Higher is slower but can improve quality.
+        cfg_scale: Classifier-free guidance scale (1-20). Higher = follow the prompt more closely.
+        sampler: Sampling method to use. One of: "DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM".
+        seed: Random seed for reproducible results. Use -1 for a random seed per call.
+        strength: Generation strength (0-1). Kept for parity; not an input image strength.
+        width: Output width in pixels (64-1216, multiple of 32 recommended).
+        height: Output height in pixels (64-1216, multiple of 32 recommended).
+
     Returns:
-        PIL Image object of the generated image, or None if generation failed.
+        A PIL.Image of the generated result. No input image is expected or required.
     """
     if prompt == "" or prompt is None:
         return None
@@ -139,10 +138,29 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', css=css) as app:
         
         # Image output area to display the generated image
         with gr.Row():
-            image_output = gr.Image(type="pil", label="Image Output", elem_id="gallery")
+            # Output component only; no input image is required by the tool
+            image_output = gr.Image(label="Image Output", elem_id="gallery")
         
-        # Bind the button to the flux_krea_generate function with the added width and height inputs
-        text_button.click(flux_krea_generate, inputs=[text_prompt, negative_prompt, steps, cfg, method, seed, strength, width, height], outputs=image_output)
+        # Bind the button to the flux_krea_generate function for the UI only
+        # Hide this event as an MCP tool to avoid schema confusion (UI wires image output)
+        text_button.click(
+            flux_krea_generate,
+            inputs=[text_prompt, negative_prompt, steps, cfg, method, seed, strength, width, height],
+            outputs=image_output,
+            show_api=False,
+            api_description=False,
+        )
+
+    # Expose a dedicated MCP/API endpoint with a clear schema (text-to-image only)
+    # This avoids clients misinterpreting the UI event as requiring an input image.
+    gr.api(
+        flux_krea_generate,
+        api_name="generate_image",
+        api_description=(
+            "Generate an image from a text prompt using FLUX.1-Krea-dev. "
+            "Inputs are text and numeric parameters only; no input image is required."
+        ),
+    )
 
 # Launch the Gradio app with MCP server enabled
 app.launch(show_api=True, share=False, mcp_server=True)