""" Script to update Basic plan subscription limits for testing rate limits and renewal flows. Updates: - LLM Calls (all providers): 10 calls (was 500-1000) - LLM Tokens (all providers): 2000 tokens (was 200k-1M) - Images: 5 images (was 50) This script updates the SubscriptionPlan table, which automatically applies to all users who have a Basic plan subscription via the plan_id foreign key. """ import sys import os from pathlib import Path from datetime import datetime, timezone # Add the backend directory to Python path backend_dir = Path(__file__).parent.parent sys.path.insert(0, str(backend_dir)) from sqlalchemy import create_engine from sqlalchemy.orm import sessionmaker from loguru import logger from models.subscription_models import SubscriptionPlan, SubscriptionTier, UserSubscription, UsageStatus from services.database import DATABASE_URL def update_basic_plan_limits(): """Update Basic plan limits for testing rate limits and renewal.""" try: engine = create_engine(DATABASE_URL, echo=False) SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine) db = SessionLocal() try: # Find Basic plan basic_plan = db.query(SubscriptionPlan).filter( SubscriptionPlan.tier == SubscriptionTier.BASIC ).first() if not basic_plan: logger.error("āŒ Basic plan not found in database!") return False # Store old values for logging old_limits = { 'gemini_calls': basic_plan.gemini_calls_limit, 'mistral_calls': basic_plan.mistral_calls_limit, 'gemini_tokens': basic_plan.gemini_tokens_limit, 'mistral_tokens': basic_plan.mistral_tokens_limit, 'stability_calls': basic_plan.stability_calls_limit, } logger.info(f"šŸ“‹ Current Basic plan limits:") logger.info(f" Gemini Calls: {old_limits['gemini_calls']}") logger.info(f" Mistral Calls: {old_limits['mistral_calls']}") logger.info(f" Gemini Tokens: {old_limits['gemini_tokens']}") logger.info(f" Mistral Tokens: {old_limits['mistral_tokens']}") logger.info(f" Images (Stability): {old_limits['stability_calls']}") # Update unified AI text generation limit to 10 basic_plan.ai_text_generation_calls_limit = 10 # Legacy per-provider limits (kept for backwards compatibility, but not used for enforcement) basic_plan.gemini_calls_limit = 1000 basic_plan.openai_calls_limit = 500 basic_plan.anthropic_calls_limit = 200 basic_plan.mistral_calls_limit = 500 # Update all LLM provider token limits to 2000 basic_plan.gemini_tokens_limit = 2000 basic_plan.openai_tokens_limit = 2000 basic_plan.anthropic_tokens_limit = 2000 basic_plan.mistral_tokens_limit = 2000 # Update image generation limit to 5 basic_plan.stability_calls_limit = 5 # Update timestamp basic_plan.updated_at = datetime.now(timezone.utc) logger.info("\nšŸ“ New Basic plan limits:") logger.info(f" LLM Calls (all providers): 10") logger.info(f" LLM Tokens (all providers): 2000") logger.info(f" Images: 5") # Count and get affected users user_subscriptions = db.query(UserSubscription).filter( UserSubscription.plan_id == basic_plan.id, UserSubscription.is_active == True ).all() affected_users = len(user_subscriptions) logger.info(f"\nšŸ‘„ Users affected: {affected_users}") if affected_users > 0: logger.info("\nšŸ“‹ Affected user IDs:") for sub in user_subscriptions: logger.info(f" - {sub.user_id}") else: logger.info(" (No active Basic plan subscriptions found)") # Commit plan limit changes first db.commit() logger.info("\nāœ… Basic plan limits updated successfully!") # Cap usage at new limits for all affected users (preserve historical data, but cap enforcement) logger.info("\nšŸ”„ Capping usage counters at new limits for Basic plan users...") logger.info(" (Historical usage preserved, but capped to allow new calls within limits)") from models.subscription_models import UsageSummary from services.subscription import PricingService pricing_service = PricingService(db) capped_count = 0 # New limits - use unified AI text generation limit if available new_call_limit = getattr(basic_plan, 'ai_text_generation_calls_limit', None) or basic_plan.gemini_calls_limit new_token_limit = basic_plan.gemini_tokens_limit # 2000 new_image_limit = basic_plan.stability_calls_limit # 5 for sub in user_subscriptions: try: # Get current billing period for this user current_period = pricing_service.get_current_billing_period(sub.user_id) or datetime.now(timezone.utc).strftime("%Y-%m") # Find usage summary for current period usage_summary = db.query(UsageSummary).filter( UsageSummary.user_id == sub.user_id, UsageSummary.billing_period == current_period ).first() if usage_summary: # Store old values for logging old_gemini = usage_summary.gemini_calls or 0 old_mistral = usage_summary.mistral_calls or 0 old_openai = usage_summary.openai_calls or 0 old_anthropic = usage_summary.anthropic_calls or 0 old_tokens = max( usage_summary.gemini_tokens or 0, usage_summary.openai_tokens or 0, usage_summary.anthropic_tokens or 0, usage_summary.mistral_tokens or 0 ) old_images = usage_summary.stability_calls or 0 # Cap LLM provider counters at new limits (don't reset, just cap) # This allows historical data to remain but prevents blocking from old usage usage_summary.gemini_calls = min(old_gemini, new_call_limit) usage_summary.mistral_calls = min(old_mistral, new_call_limit) usage_summary.openai_calls = min(old_openai, new_call_limit) usage_summary.anthropic_calls = min(old_anthropic, new_call_limit) # Cap token counters at new limits usage_summary.gemini_tokens = min(usage_summary.gemini_tokens or 0, new_token_limit) usage_summary.openai_tokens = min(usage_summary.openai_tokens or 0, new_token_limit) usage_summary.anthropic_tokens = min(usage_summary.anthropic_tokens or 0, new_token_limit) usage_summary.mistral_tokens = min(usage_summary.mistral_tokens or 0, new_token_limit) # Cap image counter at new limit usage_summary.stability_calls = min(old_images, new_image_limit) # Update totals based on capped values (approximate) # Recalculate total_calls and total_tokens based on capped provider values total_capped_calls = ( usage_summary.gemini_calls + usage_summary.mistral_calls + usage_summary.openai_calls + usage_summary.anthropic_calls + usage_summary.stability_calls ) total_capped_tokens = ( usage_summary.gemini_tokens + usage_summary.mistral_tokens + usage_summary.openai_tokens + usage_summary.anthropic_tokens ) usage_summary.total_calls = total_capped_calls usage_summary.total_tokens = total_capped_tokens # Reset status to active to allow new calls usage_summary.usage_status = UsageStatus.ACTIVE usage_summary.updated_at = datetime.now(timezone.utc) db.commit() capped_count += 1 logger.info(f" āœ… Capped usage for user {sub.user_id}:") logger.info(f" Gemini Calls: {old_gemini} → {usage_summary.gemini_calls} (limit: {new_call_limit})") logger.info(f" Mistral Calls: {old_mistral} → {usage_summary.mistral_calls} (limit: {new_call_limit})") logger.info(f" Tokens: {old_tokens} → {max(usage_summary.gemini_tokens, usage_summary.mistral_tokens)} (limit: {new_token_limit})") logger.info(f" Images: {old_images} → {usage_summary.stability_calls} (limit: {new_image_limit})") else: logger.info(f" ā„¹ļø No usage summary found for user {sub.user_id} (period {current_period})") except Exception as cap_error: logger.error(f" āŒ Error capping usage for user {sub.user_id}: {cap_error}") import traceback logger.error(traceback.format_exc()) db.rollback() if capped_count > 0: logger.info(f"\nāœ… Capped usage counters for {capped_count} user(s)") logger.info(" Historical usage preserved, but capped at new limits to allow new calls") else: logger.info("\nā„¹ļø No usage counters to cap") # Note about cache clearing logger.info("\nšŸ”„ Cache Information:") logger.info(" The subscription limits cache is per-instance and will refresh on next request.") logger.info(" No manual cache clearing needed - limits will be read from database on next check.") # Display final summary logger.info("\n" + "="*60) logger.info("BASIC PLAN UPDATE SUMMARY") logger.info("="*60) logger.info(f"\nPlan: {basic_plan.name} ({basic_plan.tier.value})") logger.info(f"Price: ${basic_plan.price_monthly}/mo, ${basic_plan.price_yearly}/yr") logger.info(f"\nUpdated Limits:") logger.info(f" LLM Calls (gemini/openai/anthropic/mistral): {basic_plan.gemini_calls_limit}") logger.info(f" LLM Tokens (gemini/openai/anthropic/mistral): {basic_plan.gemini_tokens_limit}") logger.info(f" Images (stability): {basic_plan.stability_calls_limit}") logger.info(f"\nUsers Affected: {affected_users}") logger.info("\n" + "="*60) logger.info("\nšŸ’” Note: These limits apply immediately to all Basic plan users.") logger.info(" Historical usage has been preserved but capped at new limits.") logger.info(" Users can continue making new calls up to the new limits.") logger.info(" Users will hit rate limits faster for testing purposes.") return True except Exception as e: db.rollback() logger.error(f"āŒ Error updating Basic plan: {e}") import traceback logger.error(traceback.format_exc()) raise finally: db.close() except Exception as e: logger.error(f"āŒ Failed to connect to database: {e}") import traceback logger.error(traceback.format_exc()) return False if __name__ == "__main__": logger.info("šŸš€ Starting Basic plan limits update...") logger.info("="*60) logger.info("This will update Basic plan limits for testing rate limits:") logger.info(" - LLM Calls: 10 (all providers)") logger.info(" - LLM Tokens: 2000 (all providers)") logger.info(" - Images: 5") logger.info("="*60) # Ask for confirmation in non-interactive mode, proceed directly # In interactive mode, you can add: input("\nPress Enter to continue or Ctrl+C to cancel...") try: success = update_basic_plan_limits() if success: logger.info("\nāœ… Script completed successfully!") sys.exit(0) else: logger.error("\nāŒ Script failed!") sys.exit(1) except KeyboardInterrupt: logger.info("\nāš ļø Script cancelled by user") sys.exit(1) except Exception as e: logger.error(f"\nāŒ Unexpected error: {e}") sys.exit(1)