Update run.py

run.py

@@ -1,90 +1,107 @@
-"""
-Visual Question Answering Application - Run Script for Streamlit
-"""
-
-import os
-import subprocess
-import sys
-
-# Configure minimal environment settings
-os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"  # Suppress TensorFlow logging
-
-
-def check_requirements_installed():
-    """Check if requirements are installed"""
-    try:
-        import streamlit
-        import torch
-        import transformers
-        from PIL import Image
-
-        return True
-    except ImportError as e:
-        print(f"Error: Required package not installed - {e}")
-        print("Please install requirements using: pip install -r requirements.txt")
-        return False
-
-
-def ensure_directories():
-    """Ensure all required directories exist"""
-    # Get the base directory
-    base_dir = os.path.dirname(os.path.abspath(__file__))
-
-    # Create uploads directory
-    uploads_dir = os.path.join(base_dir, "static", "uploads")
-    os.makedirs(uploads_dir, exist_ok=True)
-    print(f"Uploads directory: {uploads_dir}")
-
-    # Create logs directory
-    logs_dir = os.path.join(base_dir, "logs")
-    os.makedirs(logs_dir, exist_ok=True)
-
-
-def main():
-    """Main function to run the application"""
-    print("Visual Question Answering - Multi-Modal AI Application with Streamlit")
-
-    # Check requirements
-    if not check_requirements_installed():
-        sys.exit(1)
-
-    # Ensure directories exist
-    ensure_directories()
-
-    # Set environment variables
-    os.environ["VQA_MODEL"] = os.environ.get(
-        "VQA_MODEL", "blip"
-    )  # Default to 'blip' model
-
-    # Get the app.py path
-    app_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "app.py")
-    if not os.path.exists(app_path):
-        print(f"Error: Streamlit app not found at {app_path}")
-        sys.exit(1)
-
-    # Print startup information
-    port = int(os.environ.get("PORT", 8501))  # Streamlit default port is 8501
-    print(f"Starting VQA application on http://localhost:{port}")
-    print(f"Using VQA model: {os.environ.get('VQA_MODEL', 'blip')}")
-    print("Press Ctrl+C to exit")
-
-    # Run the Streamlit app
-    cmd = [
-        "streamlit",
-        "run",
-        app_path,
-        "--server.port",
-        str(port),
-        "--server.address",
-        "0.0.0.0",
-    ]
-    try:
-        subprocess.run(cmd)
-    except KeyboardInterrupt:
-        print("\nShutting down the application...")
-    except Exception as e:
-        print(f"Error launching Streamlit: {e}")
-
-
-if __name__ == "__main__":
-    main()
+"""
+Visual Question Answering Application - Run Script for Streamlit
+"""
+
+import os
+import subprocess
+import sys
+
+# Configure minimal environment settings
+os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"  # Suppress TensorFlow logging
+
+
+def check_requirements_installed():
+    """Check if requirements are installed"""
+    try:
+        import streamlit
+        import torch
+        import transformers
+        from PIL import Image
+
+        return True
+    except ImportError as e:
+        print(f"Error: Required package not installed - {e}")
+        print("Please install requirements using: pip install -r requirements.txt")
+        return False
+
+
+def ensure_directories():
+    """Ensure all required directories exist"""
+    # Get the base directory
+    base_dir = os.path.dirname(os.path.abspath(__file__))
+
+    # Create uploads directory
+    uploads_dir = os.path.join(base_dir, "static", "uploads")
+    os.makedirs(uploads_dir, exist_ok=True)
+    print(f"Uploads directory: {uploads_dir}")
+
+    # Create logs directory
+    logs_dir = os.path.join(base_dir, "logs")
+    os.makedirs(logs_dir, exist_ok=True)
+
+
+def is_huggingface_space():
+    """Check if the app is running on Hugging Face Spaces"""
+    return "SPACE_ID" in os.environ
+
+
+def main():
+    """Main function to run the application"""
+    print("Visual Question Answering - Multi-Modal AI Application with Streamlit")
+
+    # Check requirements
+    if not check_requirements_installed():
+        sys.exit(1)
+
+    # Ensure directories exist
+    ensure_directories()
+
+    # Set environment variables
+    os.environ["VQA_MODEL"] = os.environ.get(
+        "VQA_MODEL", "blip"
+    )  # Default to 'blip' model
+
+    # Get the app.py path
+    app_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "app.py")
+    if not os.path.exists(app_path):
+        print(f"Error: Streamlit app not found at {app_path}")
+        sys.exit(1)
+
+    # Print startup information
+    port = int(os.environ.get("PORT", 8501))  # Streamlit default port is 8501
+    print(f"Starting VQA application on http://localhost:{port}")
+    print(f"Using VQA model: {os.environ.get('VQA_MODEL', 'blip')}")
+    print("Press Ctrl+C to exit")
+
+    # Run the Streamlit app
+    if is_huggingface_space():
+        # In Hugging Face Spaces, we don't need to launch Streamlit manually
+        # Just import the app and it will be picked up by Streamlit when this script is run
+        print("Running in Hugging Face Spaces environment")
+        sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+        try:
+            # This will make the app importable by Streamlit
+            pass
+        except Exception as e:
+            print(f"Error importing app.py: {e}")
+    else:
+        # For local development, we launch Streamlit via subprocess
+        cmd = [
+            "streamlit",
+            "run",
+            app_path,
+            "--server.port",
+            str(port),
+            "--server.address",
+            "0.0.0.0",
+        ]
+        try:
+            subprocess.run(cmd)
+        except KeyboardInterrupt:
+            print("\nShutting down the application...")
+        except Exception as e:
+            print(f"Error launching Streamlit: {e}")
+
+
+if __name__ == "__main__":
+    main()