feat: Refactor data processing pipeline with AI cost tracking and enhanced session management

- Updated environment configuration to include Postgres database settings.
- Enhanced import processing to minimize field copying and rely on AI for analysis.
- Implemented detailed AI processing request tracking, including token usage and costs.
- Added new models for Question and SessionQuestion to manage user inquiries separately.
- Improved session processing scheduler with AI cost reporting functionality.
- Created a test script to validate the refactored pipeline and display processing statistics.
- Updated Prisma schema and migration files to reflect new database structure and relationships.

.env.example

@@ -20,3 +20,7 @@ IMPORT_PROCESSING_BATCH_SIZE="50"           # Number of imports to process at on
 SESSION_PROCESSING_INTERVAL="0 * * * *"     # Cron expression for AI session processing (every hour)
 SESSION_PROCESSING_BATCH_SIZE="0"           # 0 = unlimited sessions, >0 = specific limit
 SESSION_PROCESSING_CONCURRENCY="5"          # How many sessions to process in parallel
+
+# Postgres Database Configuration
+DATABASE_URL_TEST="postgresql://" 
+DATABASE_URL="postgresql://"