feat: add database mode for LLM message storage and analytics

Implements a database mode that stores LLM prompts and responses in PostgreSQL
instead of making API calls. This enables:
- Testing without consuming API credits
- Collecting analytics on usage patterns
- Development and debugging workflows

Changes:
- Added DatabaseClient class for PostgreSQL operations
- Modified LLMAnalyzer to support database/API mode toggle
- Added USE_DATABASE config flag to switch between modes
- Included Docker Compose setup for PostgreSQL
- Added utility scripts for database init and analytics viewing
- Comprehensive documentation in DATABASE_MODE.md

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

scripts/view_analytics.py

@@ -0,0 +1,67 @@
+#!/usr/bin/env python3
+"""View analytics from the message database.
+
+This script displays statistics about stored LLM messages including
+usage by company, analysis type, and time periods.
+
+Usage:
+    python scripts/view_analytics.py [--days DAYS]
+"""
+
+import sys
+import os
+import argparse
+import json
+
+# Add parent directory to path
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from SPARC import config
+from SPARC.database import DatabaseClient
+
+
+def main():
+    """Display analytics from the database."""
+    parser = argparse.ArgumentParser(description="View SPARC message analytics")
+    parser.add_argument(
+        "--days",
+        type=int,
+        default=30,
+        help="Number of days to analyze (default: 30)"
+    )
+    args = parser.parse_args()
+
+    print(f"SPARC Analytics - Last {args.days} days")
+    print("=" * 70)
+
+    try:
+        db_client = DatabaseClient(config.database_url)
+        analytics = db_client.get_analytics(days=args.days)
+
+        print(f"\nTotal Messages: {analytics['total_messages']}")
+
+        print("\nMessages by Company:")
+        if analytics['by_company']:
+            for item in analytics['by_company']:
+                company = item['company_name'] or '(unknown)'
+                print(f"  {company}: {item['count']}")
+        else:
+            print("  No data")
+
+        print("\nMessages by Analysis Type:")
+        if analytics['by_type']:
+            for item in analytics['by_type']:
+                analysis_type = item['analysis_type'] or '(unknown)'
+                print(f"  {analysis_type}: {item['count']}")
+        else:
+            print("  No data")
+
+        print("\n" + "=" * 70)
+
+    except Exception as e:
+        print(f"Error retrieving analytics: {e}")
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()