Update DeepLSD installation and add error handling

gradioChatApp.py

@@ -525,137 +525,188 @@ custom_css = """
 }
 """
 
+def check_environment():
+    """Check required environment variables and model files."""
+    required_vars = {
+        'OPENAI_API_KEY': 'OpenAI API key is required for chat functionality',
+        'STORAGE_TYPE': 'Storage type must be specified (local or azure)',
+        'USE_TORCH': 'Torch configuration must be specified'
+    }
+    
+    missing_vars = []
+    for var, message in required_vars.items():
+        if not os.getenv(var):
+            missing_vars.append(f"{var}: {message}")
+    
+    if missing_vars:
+        logger.error("Missing required environment variables:")
+        for msg in missing_vars:
+            logger.error(f"  - {msg}")
+        return False
+    
+    # Check for DeepLSD
+    try:
+        import deeplsd
+        logger.info("DeepLSD package found")
+    except ImportError:
+        logger.error("DeepLSD package not found. Please install with: pip install git+https://github.com/cvg/DeepLSD.git")
+        return False
+    
+    # Check for model files
+    model_path = "models/deeplsd_md.tar"
+    if not os.path.exists(model_path):
+        logger.error(f"Required model file not found: {model_path}")
+        return False
+    
+    return True
+
 def create_ui():
-    with gr.Blocks(css=custom_css) as demo:
-        # Logo row
-        with gr.Row(elem_classes=["logo-row"]):
-            try:
-                logo_path = os.path.join(os.path.dirname(__file__), "assets", "intuigence.png")
-                if os.path.exists(logo_path):
-                    with open(logo_path, "rb") as f:
-                        logo_base64 = base64.b64encode(f.read()).decode()
-                    gr.HTML(f"""
-                        <div style="text-align: center; padding: 10px; background-color: #1a1a1a; width: 100%;">
-                            <img src="data:image/png;base64,{logo_base64}" 
-                                 alt="Intuigence Logo" 
-                                 style="height: 60px; object-fit: contain;">
-                        </div>
-                    """)
-                else:
-                    logger.warning(f"Logo not found at {logo_path}")
-            except Exception as e:
-                logger.error(f"Error loading logo: {e}")
-
-        # Main layout
-        with gr.Row(equal_height=True, elem_classes=["full-height-row"]):
-            # Left column
-            with gr.Column(scale=2):
-                # Upload area
-                with gr.Column(elem_classes=["upload-box"]):
-                    image_input = gr.File(
-                        label="Upload P&ID Document",
-                        file_types=[".pdf", ".png", ".jpg", ".jpeg"],
-                        file_count="single",
-                        type="filepath"
-                    )
-                
-                # Status area
-                with gr.Column(elem_classes=["status-box-container"]):
-                    gr.Markdown("### Processing Status")
-                    progress_status = gr.Textbox(
-                        label="Status",
-                        show_label=False,
-                        elem_classes=["status-box"],
-                        lines=15,
-                        max_lines=20,
-                        interactive=False,
-                        autoscroll=True,
-                        value=""  # Initialize with empty value
-                    )
-                json_path_state = gr.State()
-
-            # Center column
-            with gr.Column(scale=5):
-                with gr.Tabs(elem_classes=["preview-tabs"]) as tabs:
-                    with gr.TabItem("P&ID"):
-                        original_image = gr.Image(label="Original P&ID", height=450)  # Reduced height
-                    with gr.TabItem("Symbols"):
-                        symbol_image = gr.Image(label="Detected Symbols", height=450)
-                    with gr.TabItem("Tags"):
-                        text_image = gr.Image(label="Detected Tags", height=450)
-                    with gr.TabItem("Pipelines"):
-                        line_image = gr.Image(label="Detected Lines", height=450)
-                    with gr.TabItem("Aggregated"):
-                        aggregated_image = gr.Image(label="Aggregated Results", height=450)
-                    with gr.TabItem("Graph"):
-                        graph_image = gr.Image(label="Knowledge Graph", height=450)
-
-            # Right column
-            with gr.Column(scale=3):
-                with gr.Column(elem_classes=["chat-container"]):
-                    gr.Markdown("### Chat Interface")
-                    # Initialize chat with a welcome message
-                    initial_chat = chat_message(
-                        "agent",
-                        "Ready to process P&ID documents and answer questions.",
-                        agent_avatar,
-                        get_timestamp()
-                    )
-                    chat_output = gr.HTML(
-                        label="Chat",
-                        elem_classes=["chatbox"],
-                        value=initial_chat
-                    )
-                    # Message input and send button in a fixed-height container
-                    with gr.Column(elem_classes=["chat-input-group"]):
-                        user_input = gr.Textbox(
+    """Create the Gradio interface with error handling."""
+    try:
+        # Check environment before creating UI
+        if not check_environment():
+            raise EnvironmentError("Missing required configuration. Check logs for details.")
+            
+        # Create UI components
+        with gr.Blocks(css=custom_css) as demo:
+            # Logo row
+            with gr.Row(elem_classes=["logo-row"]):
+                try:
+                    logo_path = os.path.join(os.path.dirname(__file__), "assets", "intuigence.png")
+                    if os.path.exists(logo_path):
+                        with open(logo_path, "rb") as f:
+                            logo_base64 = base64.b64encode(f.read()).decode()
+                        gr.HTML(f"""
+                            <div style="text-align: center; padding: 10px; background-color: #1a1a1a; width: 100%;">
+                                <img src="data:image/png;base64,{logo_base64}" 
+                                     alt="Intuigence Logo" 
+                                     style="height: 60px; object-fit: contain;">
+                            </div>
+                        """)
+                    else:
+                        logger.warning(f"Logo not found at {logo_path}")
+                except Exception as e:
+                    logger.error(f"Error loading logo: {e}")
+
+            # Main layout
+            with gr.Row(equal_height=True, elem_classes=["full-height-row"]):
+                # Left column
+                with gr.Column(scale=2):
+                    # Upload area
+                    with gr.Column(elem_classes=["upload-box"]):
+                        image_input = gr.File(
+                            label="Upload P&ID Document",
+                            file_types=[".pdf", ".png", ".jpg", ".jpeg"],
+                            file_count="single",
+                            type="filepath"
+                        )
+                    
+                    # Status area
+                    with gr.Column(elem_classes=["status-box-container"]):
+                        gr.Markdown("### Processing Status")
+                        progress_status = gr.Textbox(
+                            label="Status",
                             show_label=False,
-                            placeholder="Type your question here...",
-                            elem_classes=["chat-input"],
-                            lines=3
+                            elem_classes=["status-box"],
+                            lines=15,
+                            max_lines=20,
+                            interactive=False,
+                            autoscroll=True,
+                            value=""  # Initialize with empty value
                         )
-                        send_button = gr.Button(
-                            "Send",
-                            elem_classes=["send-button"]
+                    json_path_state = gr.State()
+
+                # Center column
+                with gr.Column(scale=5):
+                    with gr.Tabs(elem_classes=["preview-tabs"]) as tabs:
+                        with gr.TabItem("P&ID"):
+                            original_image = gr.Image(label="Original P&ID", height=450)  # Reduced height
+                        with gr.TabItem("Symbols"):
+                            symbol_image = gr.Image(label="Detected Symbols", height=450)
+                        with gr.TabItem("Tags"):
+                            text_image = gr.Image(label="Detected Tags", height=450)
+                        with gr.TabItem("Pipelines"):
+                            line_image = gr.Image(label="Detected Lines", height=450)
+                        with gr.TabItem("Aggregated"):
+                            aggregated_image = gr.Image(label="Aggregated Results", height=450)
+                        with gr.TabItem("Graph"):
+                            graph_image = gr.Image(label="Knowledge Graph", height=450)
+
+                # Right column
+                with gr.Column(scale=3):
+                    with gr.Column(elem_classes=["chat-container"]):
+                        gr.Markdown("### Chat Interface")
+                        # Initialize chat with a welcome message
+                        initial_chat = chat_message(
+                            "agent",
+                            "Ready to process P&ID documents and answer questions.",
+                            agent_avatar,
+                            get_timestamp()
                         )
+                        chat_output = gr.HTML(
+                            label="Chat",
+                            elem_classes=["chatbox"],
+                            value=initial_chat
+                        )
+                        # Message input and send button in a fixed-height container
+                        with gr.Column(elem_classes=["chat-input-group"]):
+                            user_input = gr.Textbox(
+                                show_label=False,
+                                placeholder="Type your question here...",
+                                elem_classes=["chat-input"],
+                                lines=3
+                            )
+                            send_button = gr.Button(
+                                "Send",
+                                elem_classes=["send-button"]
+                            )
+
+            # Set up event handlers inside the Blocks context
+            image_input.upload(
+                fn=process_pnid,
+                inputs=[image_input, progress_status],
+                outputs=[
+                    original_image,
+                    symbol_image,
+                    text_image,
+                    line_image,
+                    aggregated_image,
+                    graph_image,
+                    chat_output,
+                    progress_status,
+                    json_path_state
+                ],
+                show_progress="hidden"  # Hide the default progress bar
+            )
 
-        # Set up event handlers inside the Blocks context
-        image_input.upload(
-            fn=process_pnid,
-            inputs=[image_input, progress_status],
-            outputs=[
-                original_image,
-                symbol_image,
-                text_image,
-                line_image,
-                aggregated_image,
-                graph_image,
-                chat_output,
-                progress_status,
-                json_path_state
-            ],
-            show_progress="hidden"  # Hide the default progress bar
-        )
-
-        # Add input clearing and enable/disable logic for chat
-        def clear_and_handle_message(user_message, chat_history, json_path):
-            response = handle_user_message(user_message, chat_history, json_path)
-            return "", response  # Clear input after sending
+            # Add input clearing and enable/disable logic for chat
+            def clear_and_handle_message(user_message, chat_history, json_path):
+                response = handle_user_message(user_message, chat_history, json_path)
+                return "", response  # Clear input after sending
 
-        send_button.click(
-            fn=clear_and_handle_message,
-            inputs=[user_input, chat_output, json_path_state],
-            outputs=[user_input, chat_output]
-        )
+            send_button.click(
+                fn=clear_and_handle_message,
+                inputs=[user_input, chat_output, json_path_state],
+                outputs=[user_input, chat_output]
+            )
 
-        # Also trigger on Enter key
-        user_input.submit(
-            fn=clear_and_handle_message,
-            inputs=[user_input, chat_output, json_path_state],
-            outputs=[user_input, chat_output]
-        )
+            # Also trigger on Enter key
+            user_input.submit(
+                fn=clear_and_handle_message,
+                inputs=[user_input, chat_output, json_path_state],
+                outputs=[user_input, chat_output]
+            )
 
-    return demo
+        return demo
+    except Exception as e:
+        logger.error(f"Error creating UI: {str(e)}")
+        logger.error(traceback.format_exc())
+        # Create a minimal UI showing the error
+        with gr.Blocks() as error_demo:
+            gr.Markdown("# ⚠️ Configuration Error")
+            gr.Markdown(f"Error: {str(e)}")
+            gr.Markdown("Please check the logs and configuration.")
+        return error_demo
 
 def main():
     demo = create_ui()
@@ -668,5 +719,13 @@ if __name__ == "__main__":
     main()
 else:
     # For Spaces deployment
-    demo = create_ui()
-    app = demo.app  # Gradio requires 'app' variable for Spaces
+    try:
+        demo = create_ui()
+        app = demo.app
+    except Exception as e:
+        logger.error(f"Failed to initialize app: {str(e)}")
+        # Create minimal error app
+        with gr.Blocks() as error_demo:
+            gr.Markdown("# ⚠️ Deployment Error")
+            gr.Markdown("Failed to initialize the application.")
+        app = error_demo.app

requirements.txt

@@ -2,40 +2,29 @@
 gradio>=4.0.0
 numpy>=1.24.0
 Pillow>=8.0.0
-opencv-python-headless>=4.8.0
-PyMuPDF>=1.18.0  # for PDF processing
+opencv-python-headless>=4.8.0  # Headless version for Spaces
+PyMuPDF>=1.18.0
 
 # OCR Engines
 pytesseract>=0.3.8
 easyocr>=1.7.1
-python-doctr>=0.7.0  # For DocTR OCR
-tensorflow>=2.8.0   # Required by DocTR
+python-doctr>=0.7.0
+tensorflow>=2.8.0
 
 # Deep Learning
 torch>=2.1.0
 torchvision>=0.15.0
-ultralytics>=8.0.0  # for YOLO models
-deeplsd  # Add this for line detection
-omegaconf>=2.3.0  # Required by DeepLSD
+ultralytics>=8.0.0
+git+https://github.com/cvg/DeepLSD.git  # Install DeepLSD from GitHub
 
 # Graph Processing
 networkx>=2.6.0
 plotly>=5.3.0
 
 # Utilities
-tqdm>=4.66.0
 python-dotenv>=0.19.0
-uuid>=1.30
-shapely>=1.8.0  # for geometry operations
-
-# Azure Storage
-azure-storage-blob>=12.0.0
-azure-core>=1.24.0
-
-# AI/Chat
-openai>=1.0.0  # For ChatGPT integration
 loguru>=0.7.0
 matplotlib>=3.4.0
 
-# Added from the code block
-requests>=2.31.0
+# AI/Chat
+openai>=1.0.0