Update gptr-logs-handler.py

1. Logging Configuration: Integrated logging for better output management.

2. Clear Logs Method: Added a method to clear logs.

3. Error Handling: Enhanced error handling in the send_json method.

4. Logging Report Generation: Added logging for successful report generation.

5. Improved Readability: Overall improvements for clarity and maintainability.

tests/gptr-logs-handler.py

@@ -1,27 +1,35 @@
-from typing import Dict, Any
+import logging
+from typing import List, Dict, Any
 import asyncio
 from gpt_researcher import GPTResearcher
 
 class CustomLogsHandler:
     """A custom Logs handler class to handle JSON data."""
     def __init__(self):
-        self.logs = []  # Initialize logs to store data
+        self.logs: List[Dict[str, Any]] = []  # Initialize logs to store data
+        logging.basicConfig(level=logging.INFO)  # Set up logging configuration
 
     async def send_json(self, data: Dict[str, Any]) -> None:
-        """Send JSON data and log it."""
-        self.logs.append(data)  # Append data to logs
-        print(f"My custom Log: {data}")  # For demonstration, print the log
-
-async def run():
-    # Define the necessary parameters with sample values
-
+        """Send JSON data and log it, with error handling."""
+        try:
+            self.logs.append(data)  # Append data to logs
+            logging.info(f"My custom Log: {data}")  # Use logging instead of print
+        except Exception as e:
+            logging.error(f"Error logging data: {e}")  # Log any errors
+
+    def clear_logs(self) -> None:
+        """Clear the logs."""
+        self.logs.clear()  # Clear the logs list
+        logging.info("Logs cleared.")  # Log the clearing action
+
+async def run() -> None:
+    """Run the research process and generate a report."""
     query = "What happened in the latest burning man floods?"
-    report_type = "research_report"  # Type of report to generate
-    report_source = "online"  # Could specify source like 'online', 'books', etc.
-    tone = "informative"  # Tone of the report ('informative', 'casual', etc.)
-    config_path = None  # Path to a config file, if needed
+    report_type = "research_report"
+    report_source = "online"
+    tone = "informative"
+    config_path = None
 
-    # Initialize researcher with a custom WebSocket
     custom_logs_handler = CustomLogsHandler()
 
     researcher = GPTResearcher(
@@ -35,6 +43,7 @@ async def run():
 
     await researcher.conduct_research()  # Conduct the research
     report = await researcher.write_report()  # Write the research report
+    logging.info("Report generated successfully.")  # Log report generation
 
     return report