Conversation
- Add UserEntity with Clerk ID, rate limiting, and role management - Add CodeReviewEntity with encrypted code storage support - Add AgentFindingEntity with severity and quality metrics - Create enums: SeverityEnum, UserRole aligned with PostgreSQL ENUMs - Configure Alembic env.py for model discovery and autogenerate - Implement relationships with cascade delete for data integrity Related CGAI-15
- Create users table with Clerk ID, role, rate limiting fields - Create code_reviews table with encrypted code storage - Create agent_findings table with severity and metrics - Add PostgreSQL ENUMs: userrole, reviewstatus, severityenum - Add indexes for performance optimization - Configure cascade delete for data integrity Migration ID: ba48c1bb8e18 Related CGAI-15
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
📝 Descripción
Integración completa de Supabase PostgreSQL como base de datos de producción para CodeGuard AI. Se implementaron modelos ORM con SQLAlchemy, migraciones con Alembic, y repositorios para persistencia de análisis de código.
🎯 Historia de Usuario Relacionada
Closes #15 (CGAI-15: Supabase modelos y migraciones)
✅ Cambios Implementados
Base de Datos
DATABASE_URLUserEntity,CodeReviewEntity,AgentFindingEntityusers,code_reviews,agent_findingsRepositorios
CodeReviewRepository: CRUD para análisisAgentFindingRepository: persistencia de hallazgosAnalysisServicepara guardar resultadosAnálisis → BD
POST /api/v1/analyzeahora persiste:code_reviewscon metadata del análisisagent_findingscon cada vulnerabilidad detectadacode_contentDocumentación
WARP.md- Guía para desarrollo con Warp terminalSoftwareDesingPrinciples.instructions.md- Principios de diseño🧪 Cómo se Probó
alembic upgrade head# Análisis exitoso con persistencia POST /api/v1/analyze → 200 OK CodeReview persistido: 1754e5ab-b6a1-4dce-997a-e3e6f485f43c📋 Checklist Previo al Merge