Update app.py

app.py

@@ -220,9 +220,9 @@ def generate_image_google(
     seed: Optional[int],
 ) -> List[Image.Image]:
     """
-    This assumes your Nano-Banana / Nano-Banana-Pro image model in
-    Google AI Studio returns inline image bytes in the response.
-    Adjust parsing if your model behaves differently.
+    This assumes a Google / Nano-Banana image-capable model that returns
+    inline image bytes in the response. If your model behaves differently,
+    tweak this function.
     """
     genai = _configure_google(api_key)
     model = genai.GenerativeModel(google_image_model)
@@ -239,20 +239,28 @@ def generate_image_google(
             generation_config=generation_config or None,
         )
 
-        # Extract images from candidates
-        for cand in getattr(resp, "candidates", []):
-            for part in getattr(cand, "content", {}).parts:
+        # Extract images from candidates, but safely
+        candidates = getattr(resp, "candidates", []) or []
+        for cand in candidates:
+            content = getattr(cand, "content", None)
+            if not content:
+                continue
+            parts = getattr(content, "parts", []) or []
+            for part in parts:
                 inline = getattr(part, "inline_data", None)
                 if inline and getattr(inline, "data", None):
-                    raw = base64.b64decode(inline.data)
-                    img = Image.open(io.BytesIO(raw)).convert("RGB")
-                    images.append(img)
+                    try:
+                        raw = base64.b64decode(inline.data)
+                        img = Image.open(io.BytesIO(raw)).convert("RGB")
+                        images.append(img)
+                    except Exception:
+                        continue
 
     return images
 
 
 # -----------------------
-# Core callback
+# Core callback with provider fallback
 # -----------------------
 
 def run_generation(
@@ -291,7 +299,7 @@ def run_generation(
         full_prompt += f". Avoid: {negative_prompt.strip()}"
 
     debug_lines.append(f"Task: {task_type}")
-    debug_lines.append(f"Provider: {provider}")
+    debug_lines.append(f"Provider selected: {provider}")
     debug_lines.append(f"Preset: {preset}, Style: {style}")
     debug_lines.append(f"OpenAI size: {size}, quality: {quality}")
     debug_lines.append(f"Google image model: {google_image_model}")
@@ -322,16 +330,17 @@ def run_generation(
 
         # IMAGE
         if task_type == "Image":
-            if provider == "OpenAI":
-                if not openai_key.strip():
-                    return "Missing OpenAI API key.", [], "OpenAI key not provided."
+            primary = provider
+            secondary = "OpenAI" if provider.startswith("Google") else "Google"
 
-                # Default to GPT-Image-1; for Palantir preset, swap to DALL·E 3
+            # Helper to attempt OpenAI
+            def try_openai() -> Tuple[List[Image.Image], str]:
+                if not openai_key.strip():
+                    raise ValueError("OpenAI key missing for OpenAI image generation.")
                 image_model = "gpt-image-1"
                 if "Palantir" in preset:
                     image_model = "dall-e-3"
-
-                images = generate_image_openai(
+                imgs = generate_image_openai(
                     api_key=openai_key.strip(),
                     model=image_model,
                     prompt=full_prompt,
@@ -340,39 +349,68 @@ def run_generation(
                     n_images=n_images,
                     seed=seed_val,
                 )
-                debug_lines.append(f"OpenAI image model: {image_model}")
-            else:
+                return imgs, image_model
+
+            # Helper to attempt Google
+            def try_google() -> List[Image.Image]:
                 if not google_key.strip():
-                    return "Missing Google API key.", [], "Google key not provided."
-                images = generate_image_google(
+                    raise ValueError("Google key missing for Google image generation.")
+                model_id = google_image_model.strip() or "nano-banana-pro"
+                return generate_image_google(
                     api_key=google_key.strip(),
-                    google_image_model=google_image_model.strip() or "nano-banana-pro",
+                    google_image_model=model_id,
                     prompt=full_prompt,
                     n_images=n_images,
                     seed=seed_val,
                 )
 
+            # Try primary provider first, then fallback
+            image_model_used = None
+            try:
+                if primary == "OpenAI":
+                    images, image_model_used = try_openai()
+                else:  # Google primary
+                    images = try_google()
+            except Exception as e_primary:
+                debug_lines.append(f"Primary provider {primary} error: {e_primary}")
+                # Fallback if possible
+                try:
+                    if secondary == "OpenAI":
+                        images, image_model_used = try_openai()
+                    else:
+                        images = try_google()
+                    debug_lines.append(f"Fallback provider {secondary} succeeded.")
+                except Exception as e_secondary:
+                    debug_lines.append(f"Fallback provider {secondary} error: {e_secondary}")
+                    raise RuntimeError(
+                        f"Both providers failed. Primary: {e_primary} | Secondary: {e_secondary}"
+                    )
+
+            if image_model_used:
+                debug_lines.append(f"OpenAI image model used: {image_model_used}")
+
         if not text_output and task_type == "Image":
             text_output = (
-                "Image(s) generated. Use Text / Infographic Spec mode to "
+                "Image(s) generated. Use Text or Infographic Spec mode to "
                 "generate captions, copy, or layout specs."
             )
 
-        if not images and task_type == "Image":
-            debug_lines.append("No images returned from provider.")
+        if task_type == "Image" and not images:
+            debug_lines.append("No images returned from any provider.")
 
         return text_output, images, "\n".join(debug_lines)
 
     except Exception as e:
         debug_lines.append(f"Exception: {e}")
-        return f"Error: {e}", [], "\n".join(debug_lines)
+        # Surface the error clearly in text output as well
+        return f"Error during generation: {e}", [], "\n".join(debug_lines)
 
 
 # -----------------------
 # UI
 # -----------------------
 
-with gr.Blocks() as demo:  # <- no theme arg
+with gr.Blocks() as demo:
     gr.Markdown(
         """
 # 🧬 ZEN Omni Studio — Text • Images • Infographics
@@ -407,8 +445,8 @@ Multi-provider creator for the ZEN ecosystem:
                 label="Task Type",
             )
             provider = gr.Radio(
-                ["Google (Nano-Banana / Gemini)", "OpenAI"],
-                value="Google (Nano-Banana / Gemini)",
+                ["OpenAI", "Google (Nano-Banana / Gemini)"],
+                value="OpenAI",
                 label="Primary Provider",
             )
 
@@ -514,7 +552,7 @@ Multi-provider creator for the ZEN ecosystem:
             gr.Markdown("### 🧾 Debug / Logs")
             debug_output = gr.Textbox(
                 label="Debug Info",
-                lines=10,
+                lines=12,
             )
 
     generate_btn.click(