- Reverted to commit #10 (98e68f6) for stable AI function base
- Fixed database migrations: removed 0018-0019 that broke schema
- Fixed CreditCostConfig schema: restored credits_cost, unit fields
- Fixed historical table schema for django-simple-history
- Added debug system (staged for future use)
Changes:
- CreditCostConfig: Updated OPERATION_TYPE_CHOICES (10 ops, no duplicates)
- CreditUsageLog: Updated choices with legacy aliases marked
- Migration 0018_update_operation_choices: Applied successfully
- All AI operations working (clustering, ideas, content, optimization, etc.)
Test Results:
✓ CreditCostConfig save/load working
✓ Credit check passing for all operations
✓ AICore initialization successful
✓ AIEngine operation mapping functional
✓ Admin panel accessible without 500 errors
Future: AI-MODEL-COST-REFACTOR-PLAN.md created for token-based system
129 lines
4.0 KiB
Python
129 lines
4.0 KiB
Python
"""
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Debug logging utilities
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Fast checks with minimal overhead when debug is disabled.
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"""
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from django.core.cache import cache
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import os
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def is_debug_enabled():
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"""
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Fast check if debug logging is enabled.
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Uses cache to avoid DB queries. Returns False immediately if disabled.
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Returns:
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bool: True if debug logging enabled, False otherwise
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"""
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# Check cache first (fastest)
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cache_key = 'debug_enabled'
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enabled = cache.get(cache_key)
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# If we have a cached value (True or False), use it
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if enabled is not None:
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return bool(enabled)
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# Cache miss - check database
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try:
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from igny8_core.business.system.models import DebugConfiguration
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config = DebugConfiguration.get_config()
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enabled = config.enable_debug_logging
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# Cache the actual boolean value
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cache.set(cache_key, enabled, 60) # Cache for 1 minute
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return bool(enabled)
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except Exception as e:
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# If DB not ready or model doesn't exist, default to False
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# Cache this to avoid repeated DB errors
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cache.set(cache_key, False, 10)
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return False
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def _should_log_in_this_worker():
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"""
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Only log in the main worker to avoid duplicate logs.
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Returns True if this is the first worker or if we should always log.
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"""
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# Get worker PID - only log from worker with lowest PID to avoid duplicates
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worker_pid = os.getpid()
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# Cache the first worker PID that tries to log
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first_worker = cache.get('debug_first_worker_pid')
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if first_worker is None:
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cache.set('debug_first_worker_pid', worker_pid, 300) # Cache for 5 minutes
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return True
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# Only log if we're the first worker
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return worker_pid == first_worker
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def debug_log(message, category='general'):
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"""
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Log a debug message only if debug is enabled.
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Completely skips processing if debug is disabled.
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Args:
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message: Message to log
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category: Log category (ai_steps, api_requests, db_queries, celery_tasks)
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"""
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# Fast exit - don't even process the message if debug is disabled
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if not is_debug_enabled():
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return
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# Only log in one worker to avoid duplicates
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if not _should_log_in_this_worker():
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return
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# Check category-specific settings
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try:
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from igny8_core.business.system.models import DebugConfiguration
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config = DebugConfiguration.get_config()
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# Check category-specific flags
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if category == 'ai_steps' and not config.log_ai_steps:
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return
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if category == 'api_requests' and not config.log_api_requests:
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return
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if category == 'db_queries' and not config.log_database_queries:
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return
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if category == 'celery_tasks' and not config.log_celery_tasks:
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return
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except Exception:
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pass
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# Debug is enabled - log to console
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import sys
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import datetime
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timestamp = datetime.datetime.now().strftime("%H:%M:%S")
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worker_pid = os.getpid()
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prefix = f"[{timestamp}] [PID:{worker_pid}] [DEBUG:{category.upper()}]"
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print(f"{prefix} {message}", file=sys.stdout, flush=True)
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def debug_log_ai_step(step_name, message, **kwargs):
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"""
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Log an AI execution step only if debug is enabled.
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Completely skips processing if debug is disabled.
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Args:
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step_name: Name of the step (INIT, PREPARE, AI_CALL, etc.)
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message: Step message
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**kwargs: Additional context to log
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"""
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# Fast exit - don't even process if debug is disabled
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if not is_debug_enabled():
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return
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# Only log in one worker to avoid duplicates
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if not _should_log_in_this_worker():
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return
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# Format the message with context
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context_str = ""
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if kwargs:
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context_parts = [f"{k}={v}" for k, v in kwargs.items()]
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context_str = f" | {', '.join(context_parts)}"
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full_message = f"[{step_name}] {message}{context_str}"
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debug_log(full_message, category='ai_steps')
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