Introduce data tracking

To enable detailed analytics on user engagement and app usage, we need to track each query made by users. This will involve storing a document in our MongoDB database every time a query is executed.

Implementation Details

• Data Structure: Each document stored should contain user_id and timestamp.
• Database: MongoDB will be used to store this data (we know it and it works well).
• Schema Example: { "user_id": "<user_id_here>", "timestamp": "<ISO_date_time_here>" }

Tasks

1. Backend Update:

   • Modify the query handling mechanism to include a step for data logging.
   • Ensure the logging process is efficient and does not significantly impact query response times.
   • Implement a simple and effective schema to facilitate easy storage and retrieval of query data.

2. Data Privacy Compliance:

   • Verify that this data collection process complies with our privacy policy and any relevant data protection regulations.

The issue names no files, tests, or query entry point, so first locate the backend query-handling mechanism and existing MongoDB integration. Review the privacy requirements and determine the tracking schema and performance expectations; done means each query records the required user_id and timestamp without materially affecting responses and the collection complies with the stated privacy requirements.