Update app.py

app.py

@@ -5,21 +5,25 @@ import numpy as np
 import matplotlib.pyplot as plt
 from transformers import pipeline
 
+# Ensure log file directory is writable
+LOG_FILE = os.path.join(os.path.dirname(__file__), "phishing_urls.log")
+
 # Set up a custom logger for phishing detections
 phishing_logger = logging.getLogger('phishing')
 phishing_logger.setLevel(logging.INFO)
-phishing_handler = logging.FileHandler('phishing_urls.log')
+phishing_handler = logging.FileHandler(LOG_FILE, mode='a', force=True)  # Force flush writes
 phishing_handler.setFormatter(logging.Formatter('%(asctime)s | Confidence: %(confidence)s% | %(message)s'))
 phishing_logger.addHandler(phishing_handler)
+phishing_logger.info("Logger initialized")  # Debug log to confirm setup
 
-# Set up a separate logger for system logs (e.g., Gradio, httpx)
+# Set up a separate logger for system logs
 system_logger = logging.getLogger('system')
 system_logger.setLevel(logging.INFO)
-system_handler = logging.StreamHandler()  # Log to console; can change to FileHandler('system.log')
+system_handler = logging.StreamHandler()  # Console output
 system_handler.setFormatter(logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s'))
 system_logger.addHandler(system_handler)
 
-# Ensure root logger doesn't interfere
+# Prevent root logger interference
 logging.getLogger('').handlers = []
 
 # Initialize Hugging Face model for phishing detection
@@ -28,10 +32,12 @@ model = pipeline('text-classification', model="Ajay1311/phish")
 def log_phishing(url_or_text, confidence):
     """Log phishing URLs or content into a log file with confidence score."""
     try:
-        confidence_str = f"{float(confidence):.1f}"  # Ensure confidence is a valid float
+        confidence_str = f"{float(confidence):.1f}"  # Ensure valid float
         phishing_logger.info(f"Phishing detected: {url_or_text}", extra={'confidence': confidence_str})
+        system_logger.info(f"Logged phishing detection to {LOG_FILE}: {url_or_text} ({confidence_str}%)")
     except (ValueError, TypeError) as e:
         phishing_logger.info(f"Error logging phishing (invalid confidence): {url_or_text} | Error: {e}")
+        system_logger.error(f"Logging error: {e}")
 
 def create_speedometer_chart(confidence, is_phishing):
     """Generate speedometer chart showing confidence of phishing detection."""
@@ -113,10 +119,17 @@ def open_awareness_page():
 
 def download_log_file():
     """Return the path to the log file for download."""
-    log_file = "phishing_urls.log"
-    if os.path.exists(log_file) and os.path.getsize(log_file) > 0:
-        return log_file
-    return None, "No phishing detections logged yet."
+    try:
+        if os.path.exists(LOG_FILE):
+            # Ensure file is readable
+            os.chmod(LOG_FILE, 0o644)  # Set read/write for owner, read for others
+            if os.path.getsize(LOG_FILE) > 0:
+                return LOG_FILE
+            return None, "Log file exists but is empty. Try analyzing more inputs."
+        return None, "No phishing detections logged yet."
+    except Exception as e:
+        system_logger.error(f"Error accessing log file {LOG_FILE}: {e}")
+        return None, f"Error accessing log file: {e}"
 
 theme = gr.themes.Soft(primary_hue="blue", secondary_hue="gray").set(
     button_primary_background_fill="*primary_600",