- Added AIModelConfig model to manage AI model configurations in the database.
- Created serializers and views for AI model configurations, enabling read-only access via REST API.
- Implemented filtering capabilities for model type, provider, and default status in the API.
- Seeded initial data for text and image models, including pricing and capabilities.
- Updated Django Admin interface for managing AI models with enhanced features and bulk actions.
- Added validation methods for model and image size checks.
- Comprehensive migration created to establish the AIModelConfig model and seed initial data.
- Documented implementation and validation results in summary and report files.
- Introduced GlobalModuleSettings model for platform-wide module enable/disable settings.
- Added 'caption' field to Images model to store image captions.
- Updated GenerateImagePromptsFunction to handle new caption structure in prompts.
- Enhanced AIPromptViewSet to return global prompt types and validate active prompts.
- Modified serializers and views to accommodate new caption field and global settings.
- Updated frontend components to display captions and filter prompts based on active types.
- Created migrations for GlobalModuleSettings and added caption field to Images.
feat(admin): Add API monitoring, debug console, and system health templates for enhanced admin interface
docs: Add AI system cleanup summary and audit report detailing architecture, token management, and recommendations
docs: Introduce credits and tokens system guide outlining configuration, data flow, and monitoring strategies
- Updated AutomationService to include estimated_word_count.
- Increased stage_1_batch_size from 20 to 50 in AutomationViewSet.
- Changed Keywords model to replace 'intent' property with 'country'.
- Adjusted ClusteringService to allow a maximum of 50 keywords for clustering.
- Modified admin and management commands to remove 'intent' and use 'country' instead.
- Updated serializers to reflect the change from 'intent' to 'country'.
- Adjusted views and filters to use 'country' instead of 'intent'.
- Updated frontend forms, filters, and pages to replace 'intent' with 'country'.
- Added migration to remove 'intent' field and add 'country' field to SeedKeyword model.
- Simplified HasTenantAccess permission logic to ensure every authenticated user has an account.
- Added fallback to system account for OpenAI settings in AI configuration.
- Allowed any authenticated user to check task progress in IntegrationSettingsViewSet.
- Created a script to identify and fix orphaned users without accounts.
- Updated error response handling in business endpoints for clarity.
- Added conditional visibility for table actions based on content state (published/draft).
- Introduced `publishContent` and `unpublishContent` API functions for handling WordPress integration.
- Updated `Content` component to manage publish/unpublish actions with appropriate error handling and success notifications.
- Refactored `PostEditor` to remove deprecated SEO fields and consolidate taxonomy management.
- Enhanced `TablePageTemplate` to filter row actions based on visibility conditions.
- Updated backend API to support publishing and unpublishing content with proper status updates and external references.
- Updated AI prompts to include metadata context, cluster roles, and product attributes for improved content generation.
- Enhanced GenerateContentFunction to incorporate taxonomy and keyword objects for richer context.
- Introduced new metadata fields in frontend components for better content organization and filtering.
- Added cluster match, taxonomy match, and relevance score to LinkResults for improved link management.
- Implemented metadata completeness scoring and recommended actions in AnalysisPreview for better content optimization.
- Updated API services to support new metadata structures and site progress tracking.
- Introduced a new AI function `generate_page_content` to create structured content for website pages using JSON blocks.
- Updated `AIEngine` to handle the new function and return appropriate messages for content generation.
- Enhanced `PageGenerationService` to utilize the new AI function for generating page content based on blueprints.
- Modified `prompts.py` to include detailed content generation requirements for the new function.
- Updated site rendering logic to accommodate structured content blocks in various layouts.
- Added Linker and Optimizer apps to `INSTALLED_APPS` in `settings.py`.
- Configured API endpoints for Linker and Optimizer in `urls.py`.
- Implemented `OptimizeContentFunction` for content optimization in the AI module.
- Created prompts for content optimization and site structure generation.
- Updated `OptimizerService` to utilize the new AI function for content optimization.
- Developed frontend components including dashboards and content lists for Linker and Optimizer.
- Integrated new routes and sidebar navigation for Linker and Optimizer in the frontend.
- Enhanced content management with source and sync status filters in the Writer module.
- Comprehensive test coverage added for new features and components.
- Deleted the `import_plans.py`, `run_tests.py`, and `test_run.py` scripts as they are no longer needed.
- Updated the initial migration dependency in `0001_initial.py` to reflect recent changes in the `igny8_core_auth` app.
- Enhanced the implementation plan documentation to include new phases and updates on the site builder project.
- Updated the `vite.config.ts` and `package.json` to integrate testing configurations and dependencies for the site builder.
- Introduced a new service `igny8_site_builder` in `docker-compose.app.yml` for site building functionality, including environment variables and volume mappings.
- Deleted several outdated scripts: `create_test_users.py`, `test_image_write_access.py`, `update_free_plan.py`, and the database file `db.sqlite3` to clean up the backend.
- Updated Django settings and URL configurations to integrate the new site builder module.
- Introduced a new scheduled task for executing automation rules every 5 minutes in the Celery beat schedule.
- Updated URL routing to include a new endpoint for automation-related functionalities.
- Refactored imports in various modules to align with the new business layer structure, ensuring backward compatibility for billing models, exceptions, and services.
- CreditService.check_credits() now bypasses for:
1. System accounts (aws-admin, default-account, default)
2. Developer/admin users (if user provided)
3. Accounts with developer users (fallback for Celery tasks)
- Updated check_credits_legacy() with same bypass logic
- AIEngine credit check now uses updated CreditService
- Fixes 52 console errors caused by credit checks blocking developers
- Developers can now use AI functions without credit restrictions
- Updated CREDIT_COSTS to match Phase 0 spec (flat structure)
- Added get_credit_cost() method to CreditService
- Updated check_credits() to accept operation_type and amount
- Added deduct_credits_for_operation() convenience method
- Updated AI Engine to check credits BEFORE AI call
- Updated AI Engine to deduct credits AFTER successful execution
- Added helper methods for operation type mapping and amount calculation
- Removed hardcoded model defaults and the MODEL_CONFIG dictionary.
- Updated get_model_config() to require an account parameter and raise clear errors if IntegrationSettings are not configured.
- Eliminated unused helper functions: get_model(), get_max_tokens(), and get_temperature().
- Improved error handling to provide specific messages for missing account or model configurations.
- Cleaned up orphan exports in __init__.py to maintain a streamlined codebase.
