forked from 0xWheatyz/SPARC
0xWheatyz
44456cb073
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>
68 lines
1.8 KiB
Python
68 lines
1.8 KiB
Python
#!/usr/bin/env python3
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"""View analytics from the message database.
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This script displays statistics about stored LLM messages including
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usage by company, analysis type, and time periods.
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Usage:
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python scripts/view_analytics.py [--days DAYS]
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"""
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import sys
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import os
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import argparse
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import json
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# Add parent directory to path
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sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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from SPARC import config
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from SPARC.database import DatabaseClient
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def main():
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"""Display analytics from the database."""
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parser = argparse.ArgumentParser(description="View SPARC message analytics")
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parser.add_argument(
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"--days",
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type=int,
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default=30,
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help="Number of days to analyze (default: 30)"
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)
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args = parser.parse_args()
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print(f"SPARC Analytics - Last {args.days} days")
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print("=" * 70)
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try:
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db_client = DatabaseClient(config.database_url)
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analytics = db_client.get_analytics(days=args.days)
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print(f"\nTotal Messages: {analytics['total_messages']}")
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print("\nMessages by Company:")
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if analytics['by_company']:
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for item in analytics['by_company']:
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company = item['company_name'] or '(unknown)'
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print(f" {company}: {item['count']}")
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else:
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print(" No data")
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print("\nMessages by Analysis Type:")
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if analytics['by_type']:
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for item in analytics['by_type']:
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analysis_type = item['analysis_type'] or '(unknown)'
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print(f" {analysis_type}: {item['count']}")
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else:
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print(" No data")
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print("\n" + "=" * 70)
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except Exception as e:
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print(f"Error retrieving analytics: {e}")
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sys.exit(1)
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if __name__ == "__main__":
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main()
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