saveInteractionData

Persists user interaction data to the database for analytics and learning purposes.

This method stores individual interaction events in the interaction_data table, enabling the KARL system to learn from user behavior patterns and improve prediction accuracy over time.

Data Storage Strategy:

• Structured Logging: Each interaction stored as a discrete database record

• JSON Serialization: Complex interaction details serialized as TEXT

• Temporal Indexing: Timestamp-based organization for chronological analysis

• User Association: All interactions linked to specific user identifiers

Database Operation:

INSERT INTO interaction_data (user_id, type, details, timestamp)
VALUES (?, ?, ?, ?)

Data Mapping:

• user_id ← InteractionData.userId

• type ← InteractionData.type (interaction classification)

• details ← InteractionData.details.toString() (serialized map)

• timestamp ← InteractionData.timestamp (Unix epoch time)

Interaction Types & Examples:

• "command_prediction": AI-generated command suggestions

• "user_acceptance": User accepted/rejected predictions

• "context_change": Directory or environment changes

• "feedback_submission": Explicit user feedback events

• "error_recovery": Error handling and recovery actions

Threading & Performance:

• Asynchronous: Non-blocking operation on Dispatchers.IO

• Prepared Statements: SQL injection prevention and performance optimization

• Resource Management: Automatic statement cleanup after execution

Error Handling:

• SQLException: Database operation failures with detailed error logging

• Exception Propagation: Errors re-thrown to calling context

• Data Integrity: Failed insertions do not affect existing data

Analytics & Learning Implications:

• Pattern Recognition: Enables ML algorithms to identify usage patterns

• Prediction Improvement: Historical data improves future suggestions

• User Profiling: Builds user-specific behavioral models

• System Optimization: Identifies common workflows and pain points

Data Retention Considerations:

• Storage Growth: Interaction data accumulates over time

• Privacy: Contains user behavior information requiring careful handling

• Cleanup: Consider implementing data retention policies

Parameters

See also

Throws