Update app.py

app.py

@@ -630,7 +630,7 @@ CSS_STYLES = """
     }
     /* Default: add subtitle under titles */
     .gradio-container h1::after {
-    content: "Fetch Webpage | Search DuckDuckGo | Code Interpreter | Kokoro TTS | Flux Krea (Serverless)";
+    content: "Fetch Webpage | Search DuckDuckGo | Code Interpreter | Kokoro TTS | Image Generation";
         display: block;
         font-size: 1rem;
         font-weight: 500;
@@ -665,14 +665,15 @@ kokoro_interface = gr.Interface(
 )
 
 # ==========================
-# Flux Krea (Serverless)
+# Image Generation (Serverless)
 # ==========================
 
 HF_API_TOKEN = os.getenv("HF_READ_TOKEN")
 
 
-def Flux_Krea_Generate(  # <-- MCP tool #5 (Flux Krea - Serverless)
+def Image_Generation(  # <-- MCP tool #5 (Image Generation)
     prompt: Annotated[str, "Text description of the image to generate."],
+    model_id: Annotated[str, "Hugging Face model id in the form 'creator/model-name' (e.g., black-forest-labs/FLUX.1-Krea-dev)."] = "black-forest-labs/FLUX.1-Krea-dev",
     negative_prompt: Annotated[str, "What should NOT appear in the image." ] = (
         "(deformed, distorted, disfigured), poorly drawn, bad anatomy, wrong anatomy, extra limb, "
         "missing limb, floating limbs, (mutated hands and fingers), disconnected limbs, mutation, "
@@ -686,8 +687,9 @@ def Flux_Krea_Generate(  # <-- MCP tool #5 (Flux Krea - Serverless)
     height: Annotated[int, "Output height in pixels (64–1216, multiple of 32 recommended)."] = 1024,
 ) -> Image.Image:
     """
-    Generate a single image from a text prompt using the black-forest-labs/FLUX.1-Krea-dev
-    model via Hugging Face Inference (serverless). Returns a PIL image.
+    Generate a single image from a text prompt using a Hugging Face model via
+    serverless Inference. Returns a PIL image. By default, the model is
+    black-forest-labs/FLUX.1-Krea-dev.
 
     Notes (MCP):
     - Per the latest Gradio MCP docs, images returned from tools are handled by the server and
@@ -696,6 +698,8 @@ def Flux_Krea_Generate(  # <-- MCP tool #5 (Flux Krea - Serverless)
 
     Args:
         prompt (str): Text description of the image to generate.
+        model_id (str): The Hugging Face model id (creator/model-name). Defaults to
+            "black-forest-labs/FLUX.1-Krea-dev".
         negative_prompt (str): What should NOT appear in the image.
         steps (int): Number of denoising steps (1–100). Higher can improve quality.
         cfg_scale (float): Guidance scale (1–20). Higher = follow the prompt more closely.
@@ -726,7 +730,7 @@ def Flux_Krea_Generate(  # <-- MCP tool #5 (Flux Krea - Serverless)
             image = client.text_to_image(
                 prompt=enhanced_prompt,
                 negative_prompt=negative_prompt,
-                model="black-forest-labs/FLUX.1-Krea-dev",
+                model=model_id,
                 width=width,
                 height=height,
                 num_inference_steps=steps,
@@ -741,7 +745,7 @@ def Flux_Krea_Generate(  # <-- MCP tool #5 (Flux Krea - Serverless)
     # If we reach here, all providers failed
     msg = str(last_error) if last_error else "Unknown error"
     if "404" in msg:
-        raise gr.Error("Model not found. Ensure 'FLUX.1-Krea-dev' is accessible with your HF token.")
+        raise gr.Error(f"Model not found or unavailable: {model_id}. Check the id and your HF token access.")
     if "503" in msg:
         raise gr.Error("The model is warming up. Please try again shortly.")
     if "401" in msg or "403" in msg:
@@ -749,10 +753,11 @@ def Flux_Krea_Generate(  # <-- MCP tool #5 (Flux Krea - Serverless)
     raise gr.Error(f"Image generation failed: {msg}")
 
 
-flux_krea_interface = gr.Interface(
-    fn=Flux_Krea_Generate,
+image_generation_interface = gr.Interface(
+    fn=Image_Generation,
     inputs=[
         gr.Textbox(label="Prompt", placeholder="Enter a prompt", lines=2),
+        gr.Textbox(label="Model", value="black-forest-labs/FLUX.1-Krea-dev", placeholder="creator/model-name"),
         gr.Textbox(
             label="Negative Prompt",
             value=(
@@ -772,28 +777,28 @@ flux_krea_interface = gr.Interface(
         gr.Slider(minimum=64, maximum=1216, value=1024, step=32, label="Height"),
     ],
     outputs=gr.Image(label="Generated Image"),
-    title="Flux Krea (Serverless)",
+    title="Image Generation",
     description=(
-        "<div style=\"text-align:center\">Generate images with FLUX.1-Krea-dev via Hugging Face Inference. "
-        "No input image required. 'Strength' is omitted. Set HF_READ_TOKEN as needed.</div>"
+        "<div style=\"text-align:center\">Generate images via Hugging Face Inference. "
+        "Default model: black-forest-labs/FLUX.1-Krea-dev. Set HF_READ_TOKEN as needed.</div>"
     ),
     api_description=(
-        "Generate a single image from a text prompt using black-forest-labs/FLUX.1-Krea-dev on Hugging Face Inference. "
-        "Parameters: prompt (str), negative_prompt (str), steps (int, 1–100), cfg_scale (float, 1–20), "
+        "Generate a single image from a text prompt using a Hugging Face model (serverless Inference). "
+        "Parameters: prompt (str), model_id (str, creator/model-name), negative_prompt (str), steps (int, 1–100), cfg_scale (float, 1–20), "
         "sampler (str, label only), seed (int, -1=random), width/height (int, 64–1216). Returns a PIL.Image."
     ),
     allow_flagging="never",
 )
 
-# Build tabbed app including Flux Krea
+# Build tabbed app including Image Generation
 demo = gr.TabbedInterface(
-    interface_list=[fetch_interface, concise_interface, code_interface, kokoro_interface, flux_krea_interface],
+    interface_list=[fetch_interface, concise_interface, code_interface, kokoro_interface, image_generation_interface],
     tab_names=[
         "Fetch Webpage",
         "DuckDuckGo Search",
         "Python Code Executor",
         "Kokoro TTS",
-        "Flux Krea (Serverless)",
+        "Image Generation",
     ],
     title="Tools MCP",
     theme="Nymbo/Nymbo_Theme",