Update app.py

app.py

@@ -14,133 +14,137 @@ os.environ['REPLICATE_API_TOKEN'] = os.getenv('REPLICATE_API_TOKEN')
 def upload_to_imgur(image):
     """
     Upload image to Imgur and return URL
-    Alternative: You can use other services like Cloudinary, imgbb, etc.
     """
-    import base64
-    import json
-    
-    # Convert PIL image to base64
-    buffered = BytesIO()
-    image.save(buffered, format="PNG")
-    img_base64 = base64.b64encode(buffered.getvalue()).decode()
-    
-    # Imgur API (anonymous upload)
-    headers = {
-        'Authorization': 'Client-ID 0d90e8a3e7d8b4e'  # Public client ID for anonymous uploads
-    }
-    
-    response = requests.post(
-        'https://api.imgur.com/3/image',
-        headers=headers,
-        data={'image': img_base64}
-    )
-    
-    if response.status_code == 200:
-        data = response.json()
-        return data['data']['link']
-    else:
-        raise Exception(f"Failed to upload to Imgur: {response.status_code}")
+    try:
+        # Convert PIL image to base64
+        buffered = BytesIO()
+        image.save(buffered, format="PNG")
+        buffered.seek(0)
+        img_base64 = base64.b64encode(buffered.getvalue()).decode()
+        
+        # Imgur API (anonymous upload)
+        headers = {
+            'Authorization': 'Client-ID 0d90e8a3e7d8b4e'  # Public client ID
+        }
+        
+        response = requests.post(
+            'https://api.imgur.com/3/image',
+            headers=headers,
+            data={'image': img_base64}
+        )
+        
+        if response.status_code == 200:
+            data = response.json()
+            return data['data']['link']
+    except:
+        pass
+    return None
+
+def save_temp_image(image):
+    """
+    Save image temporarily and return file path
+    """
+    with tempfile.NamedTemporaryFile(suffix='.png', delete=False) as tmp:
+        image.save(tmp.name, 'PNG')
+        return tmp.name
 
 def process_images(prompt, image1, image2=None):
     """
     Process uploaded images with Replicate API
     """
     if not image1:
-        return None, "Please upload at least one image"
+        return None, "❌ Please upload at least one image"
     
     # Check if API token is set
     if not os.getenv('REPLICATE_API_TOKEN'):
         return None, "⚠️ Please set REPLICATE_API_TOKEN environment variable"
     
     try:
-        status_message = "📤 Uploading images..."
-        
-        # Upload images to get public URLs
+        # Prepare image URLs list
         image_urls = []
         
-        try:
-            # Try to upload to Imgur (or your preferred service)
-            url1 = upload_to_imgur(image1)
+        # Try to upload images to Imgur to get public URLs
+        url1 = upload_to_imgur(image1)
+        if url1:
             image_urls.append(url1)
-            
-            if image2:
-                url2 = upload_to_imgur(image2)
-                image_urls.append(url2)
-                
-        except Exception as upload_error:
-            # Fallback: Convert to base64 data URIs
-            buffered1 = BytesIO()
-            image1.save(buffered1, format="PNG")
-            img_base64_1 = base64.b64encode(buffered1.getvalue()).decode()
-            image_urls.append(f"data:image/png;base64,{img_base64_1}")
-            
-            if image2:
-                buffered2 = BytesIO()
-                image2.save(buffered2, format="PNG")
-                img_base64_2 = base64.b64encode(buffered2.getvalue()).decode()
-                image_urls.append(f"data:image/png;base64,{img_base64_2}")
+        else:
+            # If Imgur fails, you need to use another service or local server
+            # For now, we'll save locally (note: this won't work with Replicate)
+            return None, "⚠️ Image hosting failed. Please try again or use a different hosting service."
         
-        status_message = "🎨 Processing with nano-banana model..."
+        if image2:
+            url2 = upload_to_imgur(image2)
+            if url2:
+                image_urls.append(url2)
         
-        # Prepare input matching the exact format from your example
+        # Prepare input exactly as shown in your example
         input_data = {
             "prompt": prompt,
             "image_input": image_urls
         }
         
-        # Run the model
+        print(f"Sending to Replicate: {input_data}")
+        
+        # Run the model exactly as in your example
         output = replicate.run(
             "google/nano-banana",
             input=input_data
         )
         
-        # Handle various output formats
-        output_url = None
+        # Process output - based on your example, output should have url() and read() methods
+        if output is None:
+            return None, "❌ No output received from model"
+        
+        # Try different methods to get the image
+        try:
+            # Method 1: Using read() method as in your example
+            if hasattr(output, 'read'):
+                img_data = output.read()
+                img = Image.open(BytesIO(img_data))
+                return img, "✅ Image generated successfully using nano-banana!"
+        except:
+            pass
+        
+        try:
+            # Method 2: Using url() method and downloading
+            if hasattr(output, 'url'):
+                output_url = output.url()
+                response = requests.get(output_url, timeout=30)
+                if response.status_code == 200:
+                    img = Image.open(BytesIO(response.content))
+                    return img, "✅ Image generated successfully using nano-banana!"
+        except:
+            pass
         
-        # Check different possible output formats
-        if hasattr(output, 'url'):
-            output_url = output.url()
-        elif isinstance(output, str):
+        # Method 3: If output is a URL string or list
+        output_url = None
+        if isinstance(output, str):
             output_url = output
         elif isinstance(output, list) and len(output) > 0:
             output_url = output[0]
-        elif hasattr(output, '__iter__'):
-            try:
-                for item in output:
-                    if isinstance(item, str) and item.startswith('http'):
-                        output_url = item
-                        break
-            except:
-                pass
         
-        if not output_url:
-            return None, f"❌ Error: No valid output URL found. Response type: {type(output)}"
-        
-        # Download the generated image
-        if hasattr(output, 'read'):
-            # If output has a read method, use it
-            img_data = output.read()
-            img = Image.open(BytesIO(img_data))
-        else:
-            # Otherwise, download from URL
-            response = requests.get(output_url)
+        if output_url:
+            response = requests.get(output_url, timeout=30)
             if response.status_code == 200:
                 img = Image.open(BytesIO(response.content))
-            else:
-                return None, f"❌ Error: Failed to download image (Status: {response.status_code})"
+                return img, "✅ Image generated successfully using nano-banana!"
         
-        return img, f"✅ Image generated successfully! Output URL: {output_url[:50]}..."
+        return None, f"❌ Could not process output. Output type: {type(output)}"
         
-    except replicate.exceptions.ModelError as e:
-        return None, f"❌ Model Error: {str(e)}\n\nMake sure 'google/nano-banana' exists and is accessible."
-    except Exception as e:
+    except replicate.exceptions.ReplicateError as e:
         error_msg = str(e)
-        if "not found" in error_msg.lower():
-            return None, "❌ Model 'google/nano-banana' not found. Please check:\n1. Model name is correct\n2. Model is public or you have access\n3. Try format: 'owner/model-name'"
-        elif "authentication" in error_msg.lower():
-            return None, "❌ Authentication failed. Please check your REPLICATE_API_TOKEN."
+        if "502" in error_msg:
+            return None, "❌ Server error (502). The model might be unavailable. Please try again later."
+        elif "404" in error_msg:
+            return None, "❌ Model 'google/nano-banana' not found. Please verify the model exists."
+        elif "401" in error_msg or "403" in error_msg:
+            return None, "❌ Authentication error. Please check your REPLICATE_API_TOKEN."
+        elif "402" in error_msg:
+            return None, "❌ Payment required. Please check your Replicate billing status."
         else:
-            return None, f"❌ Error: {error_msg}"
+            return None, f"❌ Replicate Error: {error_msg}"
+    except Exception as e:
+        return None, f"❌ Error: {str(e)}"
 
 # Create Gradio interface with gradient theme
 css = """
@@ -189,7 +193,7 @@ with gr.Blocks(css=css, theme=gr.themes.Soft()) as demo:
         <div class="header-text">🎨 AI Image Style Transfer Studio</div>
         <div class="description-text">
             Upload 1-2 images and describe how you want them styled.
-            The AI will create a beautiful transformation!
+            The AI will create a beautiful transformation using nano-banana model!
         </div>
     """)
     
@@ -226,7 +230,7 @@ with gr.Blocks(css=css, theme=gr.themes.Soft()) as demo:
             #### 💡 Tips:
             - Upload high-quality images for best results
             - Be specific in your style description
-            - Experiment with different prompts!
+            - Model: google/nano-banana
             """)
         
         with gr.Column(scale=1):
@@ -248,10 +252,10 @@ with gr.Blocks(css=css, theme=gr.themes.Soft()) as demo:
     with gr.Row():
         gr.Examples(
             examples=[
+                ["Make the sheets in the style of the logo. Make the scene natural.", None, None],
                 ["Transform into watercolor painting style", None, None],
                 ["Make it look like a vintage photograph", None, None],
                 ["Apply cyberpunk neon style", None, None],
-                ["Convert to minimalist line art", None, None],
             ],
             inputs=[prompt, image1, image2],
             label="Example Prompts"
@@ -272,7 +276,7 @@ with gr.Blocks(css=css, theme=gr.themes.Soft()) as demo:
     
     1. **Set Environment Variable:**
        ```bash
-       export REPLICATE_API_TOKEN="your_api_token_here"
+       export REPLICATE_API_TOKEN="r8_your_token_here"
        ```
        Get your token from: https://replicate.com/account/api-tokens
     
@@ -281,22 +285,21 @@ with gr.Blocks(css=css, theme=gr.themes.Soft()) as demo:
        pip install gradio replicate pillow requests
        ```
     
-    3. **Image Hosting Options:**
-       - **Option A**: Uses Imgur for free image hosting (default)
-       - **Option B**: Falls back to base64 data URIs if upload fails
-       - **Option C**: Use your own image hosting service (Cloudinary, S3, etc.)
+    3. **Model Information:**
+       - Model: `google/nano-banana`
+       - Input format: 
+         - `prompt`: Text description
+         - `image_input`: List of image URLs
+       - Output: Generated/styled image
     
-    4. **Model Notes:**
-       - Using: `google/nano-banana` model
-       - If this model doesn't exist, try:
-         - `stability-ai/stable-diffusion`
-         - `pharmapsychotic/clip-interrogator`
-         - Check available models at: https://replicate.com/explore
+    4. **Important Notes:**
+       - Images must be hosted with public URLs
+       - Currently using Imgur for free image hosting
+       - If model returns 502 error, it may be temporarily unavailable
     
     ### 🔒 Security:
     - API keys are managed through environment variables
     - Never commit API keys to version control
-    - Consider implementing user authentication for production
     """)
 
 # Launch the app