Update app.py

app.py

@@ -1,61 +1,72 @@
 import gradio as gr
 from gradio_client import Client
+from PIL import Image
+import requests
+from io import BytesIO
 
-# Connect to your deployed Gradio apps
+# Connect to remote Gradio apps
 grounded_client = Client("admin08077/veo")
 image_client = Client("admin08077/picgenai")
 chat_client = Client("admin08077/genai")
 
 def generate_book(topic):
-    # Step 1: Get grounded info
+    # 1. Grounded response
     try:
         grounded_response = grounded_client.predict(
             prompt=topic,
             api_name="/generate_grounded_response"
         )
     except Exception as e:
-        grounded_response = f"❌ Error getting grounded response: {e}"
+        grounded_response = f"Error: {e}"
 
-    # Step 2: Get image + caption
+    # 2. Image and caption
     try:
-        result = image_client.predict(
+        caption, image = image_client.predict(
             prompt=topic,
             api_name="/generate_image_and_caption"
         )
-        if isinstance(result, (list, tuple)) and len(result) == 2:
-            image_url_or_path, caption = result
-        else:
-            image_url_or_path, caption = None, "⚠️ Unexpected image format."
+
+        # Image might come back as file path or PIL.Image — normalize it
+        if isinstance(image, str):  # handle file path
+            if image.startswith("http"):
+                response = requests.get(image)
+                image = Image.open(BytesIO(response.content))
+            else:
+                image = Image.open(image)
+
     except Exception as e:
-        image_url_or_path, caption = None, f"❌ Error generating image: {e}"
+        caption = f"Error generating image: {e}"
+        image = None
 
-    # Step 3: Get story content
+    # 3. Gemini story
     try:
-        gemini_narrative = chat_client.predict(
-            user_input=f"Write a short story based on: {topic}",
+        narrative = chat_client.predict(
+            user_input=f"Write a short story about: {topic}",
             api_name="/chat_with_gemini"
         )
     except Exception as e:
-        gemini_narrative = f"❌ Error generating narrative: {e}"
+        narrative = f"Error: {e}"
 
-    return grounded_response, image_url_or_path, caption, gemini_narrative
+    # Return all parts
+    return grounded_response, caption, image, narrative
 
-with gr.Blocks() as demo:
-    gr.Markdown("## 📘 AI-Generated Illustrated Book")
+# Gradio UI
+with gr.Blocks(title="📘 AI-Generated Mini Book") as demo:
+    gr.Markdown("## 📘 Generate a Mini Illustrated Book with Gemini + Gradio Clients")
 
-    topic_input = gr.Textbox(label="Book Topic", placeholder="e.g. Who won Euro 2024?")
-    generate_btn = gr.Button("📚 Generate Book")
+    with gr.Row():
+        topic_input = gr.Textbox(label="Book Topic", placeholder="e.g. Who won Euro 2024?")
+        generate_button = gr.Button("Generate Book")
 
-    with gr.Column():
-        grounded_output = gr.Textbox(label="🌐 Chapter 1: Grounded Facts", lines=4)
-        image_output = gr.Image(label="🖼️ Chapter 2: Illustration")
-        caption_output = gr.Textbox(label="Image Caption")
-        narrative_output = gr.Textbox(label="✍️ Chapter 3: Story", lines=10)
+    grounded_output = gr.Textbox(label="🌍 Grounded Info", lines=3)
+    caption_output = gr.Textbox(label="🖼️ Image Caption")
+    image_output = gr.Image(label="📷 Illustration", type="pil")
+    story_output = gr.Textbox(label="📖 Story", lines=8)
 
-    generate_btn.click(
+    generate_button.click(
         fn=generate_book,
         inputs=topic_input,
-        outputs=[grounded_output, image_output, caption_output, narrative_output]
+        outputs=[grounded_output, caption_output, image_output, story_output]
     )
 
 demo.launch()