Description
Current logging isn't sufficient for detailed debugging or monitoring of the R2R pipelines and queries:
I'd like more detail on the details of what is happening in response to a query. What is the additional context being provided by RAG? When agents are involved can I see the individual agent interactions with the LLM in the log? (which might be a deeper level of detail than a summary of interactions, so multiple logging levels would be helpful.)
I would like to see the generated Cypher queries and the internal map-reduce queries
The logging levels could be:
TRACE: The most detailed level, capturing every action and event within the application.
DEBUG: Provides more granular information than TRACE, often used for troubleshooting specific components or functionalities.
INFO: Logs informational messages about the application's progress and state.
WARNING: Indicates potential problems or unexpected behavior that might not be critical but should be investigated.
ERROR: Records error messages when something goes wrong, providing essential details for debugging.
CRITICAL: Logs severe errors that could prevent the application from functioning correctly.
Other suggestions...
Use a Structured Logging Format: Consider using a structured logging format (e.g., JSON) to make it easier to parse and analyze log data.
Rotate Log Files: Implement log rotation to prevent log files from becoming excessively large.
Consider a Logging Framework: Explore logging frameworks like Python's logging module or third-party options for advanced features and customization.
Leverage Debugging Tools: Utilize debugging tools (e.g., debuggers, profilers) in conjunction with logging to gain deeper insights into application behavior.
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